高空西北气流下铜仁东部特大暴雨的预报分析及思考          下载免费PDF全文

徐大红  胡萍  杨群  李习瑾 《中低纬山地气象》2022,46(2):9-17

利用贵州省预报业务常规、地面自动站加密观测资料、NCEP/FNL1°×1°再分析资料、业务数值预报模式,分析2020年6月29日铜仁市东部高空西北气流影响下的特大暴雨环境场特征、地面中小尺度场特征以及3家数值预报模式检验,初步分析产生此次特大暴雨的可能成因是在副高东南退、东北冷涡槽后高空西北气流维持、低层冷平流下传西输、地面辐合维持增强为涡旋、地面东路弱冷空气侵入、能量锋区斜压性增强;短临监测发现雷达回波有列车效应、低层辐合高层辐散的共轭配置、中层气旋式辐合;初步得出了西北气流影响下弱天气尺度环境场的铜仁市东部暴雨的预报着眼点。  相似文献   

The Interannual Variation of Transboundary Contributions from Chinese Emissions of PM_(2.5) to South Korea     

Xiao HAN  Meigen ZHANG 《大气科学进展》2021,38(5):701-706

In recent years,several studies pointed out that anthropogenic emission sources in China which significantly contribute to the PM_2.5mass burden was an important cause of particulate pollution in South Korea.However,most studies generally focused upon a single pollution event.It is rare to see comprehensive research that captures those features prone to interannual variations concerning the transboundary pollutant contribution in South Korea using a unified method.In this paper,we establish the emission inventories covering East Asia in 2010,2015,and 2017,and then conduct the source apportionment by applying a coupled regional air quality model called the Integrated Source Apportionment Module(ISAM).Comparison of simulated and observed PM_2.5mass concentration at 165 CNEMC(China National Environmental Monitoring Center)sites suggests that the PM_2.5concentrations are well represented by the modeling system.The model is used to quantitatively investigate the contribution from emission sources in China to PM_2.5concentrations over South Korea and those features found to be prone to interannual variations are then discussed.The results show that the average annual contribution of PM_2.5has dropped significantly from 28.0%in 2010 to 15.7%in 2017,which strongly suggests that China has achieved remarkable results in the treatment of atmospheric particulates.  相似文献   

Record Arctic Ozone Loss in Spring 2020 is Likely Caused by North Pacific Warm Sea Surface Temperature Anomalies     

Yan XIA  Yongyun HU  Jiankai ZHANG  Fei XIE  Wenshou TIAN 《大气科学进展》2021,38(10):1723-1736

Record ozone loss was observed in the Arctic stratosphere in spring 2020. This study aims to determine what caused the extreme Arctic ozone loss. Observations and simulation results are examined in order to show that the extreme Arctic ozone loss was likely caused by record-high sea surface temperatures(SSTs) in the North Pacific. It is found that the record Arctic ozone loss was associated with the extremely cold and persistent stratospheric polar vortex over February–April, and the extremely cold vortex was a result of anomalously weak planetary wave activity. Further analysis reveals that the weak wave activity can be traced to anomalously warm SSTs in the North Pacific. Both observations and simulations show that warm SST anomalies in the North Pacific could have caused the weakening of wavenumber-1 wave activity, colder Arctic vortex, and lower Arctic ozone. These results suggest that for the present-day level of ozone-depleting substances, severe Arctic ozone loss could form again, as long as certain dynamic conditions are satisfied.  相似文献   

Homogenization of the Daily Land Surface Temperature over the Mainland of China from 1960 through 2017     

Dan WANG  Aihui WANG  Xianghui KONG 《大气科学进展》2021,38(11):1811-1822

Land surface temperature(LST) is one of the most important factors in the land-atmosphere interaction process. Raw measured LSTs may contain biases due to instrument replacement, changes in recording procedures, and other non-climatic factors. This study attempts to reduce the above biases in raw daily measurements and achieves a homogenized daily LST dataset over China using 2360 stations from 1960 through 2017. The high-quality land surface air temperature(LSAT)dataset is used to correct the LST warming biases especially evident during cold months in regions north of 40°N due to the replacement of observation instruments around 2004. Subsequently, the Multiple Analysis of Series for Homogenization(MASH) method is adopted to detect and then adjust the daily observed LST records. In total, 3.68 × 103 effective breakpoints in 1.65 × 106 monthly records(about 20%) are detected. A large number of these effective breakpoints are located over large parts of the Sichuan Basin and southern China. After the MASH procedure, LSTs at more than 80% of the breakpoints are adjusted within +/– 0.5°C, and of the remaining breakpoints, only 10% are adjusted over 1.5°C.Compared to the raw LST dataset over the whole domain, the homogenization significantly reduces the mean LST magnitude and its interannual variability as well as its linear trend at most stations. Finally, we perform preliminary analysis upon the homogenized LST and find that the annual mean LST averaged across China shows a significant warming trend [0.22°C(10 yr)–1]. The homogenized LST dataset can be further adapted for a variety of applications(e.g.,model evaluation and extreme event characterization).  相似文献   

Influence of Sea Surface Temperature on the Predictability of Idealized Tropical Cyclone Intensity     

钟权加  李建平  李舒文  王羱  丁瑞强  张立凤 《热带气象学报(英文版)》2021,27(4):355-367

The role of sea surface temperature (SST) forcing in the development and predictability of tropical cyclone (TC) intensity is examined using a large set of idealized numerical experiments in the Weather Research and Forecasting (WRF) model. The results indicate that the onset time of rapid intensification of TC gradually decreases, and the peak intensity of TC gradually increases, with the increased magnitude of SST. The predictability limits of the maximum 10 m wind speed (MWS) and minimum sea level pressure (MSLP) are ~72 and ~84 hours, respectively. Comparisons of the analyses of variance for different simulation time confirm that the MWS and MSLP have strong signal-to-noise ratios (SNR) from 0-72 hours and a marked decrease beyond 72 hours. For the horizontal and vertical structures of wind speed, noticeable decreases in the magnitude of SNR can be seen as the simulation time increases, similar to that of the SLP or perturbation pressure. These results indicate that the SST as an external forcing signal plays an important role in TC intensity for up to 72 hours, and it is significantly weakened if the simulation time exceeds the predictability limits of TC intensity.  相似文献   

浅谈多传感器融合技术在气象观测中应用          下载免费PDF全文

张瑞  蒲小兰  周宇 《中低纬山地气象》2022,46(2):118-120

多传感器融合技术现阶段在气象观测中的应用主要体现在气温降水多传感器上,多传感器的正式运行减轻了地面气象观测人工维护工作量,确保气温与雨量数据的完整性,但在使用中发现多传感器融合观测存在的一些问题,如果能完善解决这些问题,则能进一步提高气温降水观测数据的准确性,实现全方位地面观测自动化。  相似文献   

基于多模式集成冬半年气温预报偏差修正     

齐铎  刘松涛  赵广娜  高梦竹 《气象与环境学报》2022,38(3):119-126

卡尔曼滤波递减平均方法对模式直接输出的气温预报进行订正,能有效提高预报准确率,但有时会造成显著负订正的现象,使订正预报效果反而不及模式直接输出。利用消除偏差集合平均方法(BREM)选择最优滑动训练期对2019年10月至2020年4月ECMWF预报(EC)、经过卡尔曼滤波递减平均法订正的预报(EC_COR)及中央台网格指导预报(SCMOC)等3种气温预报在黑龙江省的结果进行集成,并将BREM方法对EC_COR的修正效果进行评估,结果表明:不同预报结果都表现为冬季和夜间预报的准确率更低,气温偏低的11月至翌年1月更倾向于表现出预报较实况系统性偏高的特点。BREM方法能有效地修正EC_COR对EC负订正的现象,且可显著高于任何一种参与集成的单一预报效果。可在对单一模式进行卡尔曼滤波递减平均订正的基础上,进一步提升预报质量。另外,利用集成方法对高质量预报产品的融合(不局限于模式直接输出预报或是订正预报)可获取较单一预报更优的预报结果。  相似文献   

Uncertainty in projections of the South Asian summer monsoon under global warming by CMIP6 models: Role of tropospheric meridional thermal contrast          下载免费PDF全文

Yunqi Kong  Yuting Wu  Xiaoming Hu  Yana Li  Song Yang 《大气和海洋科学快报》2022,15(1):100145

本文基于第六次国际耦合模式比较计划共18个模式的工业革命前实验和CO₂浓度突然四倍实验,发现在CO₂四倍强迫下,南亚夏季风环流呈显著减弱趋势,但减弱强度存在较大模式间差异.利用Webster-Yang指数和经向哈得莱环流指数的下降趋势表征SASM减弱强度,发现该下降趋势与欧亚大陆-印度洋之间对流层上层经向温度梯度的变化值(EUTT-IUTT)高度相关.进一步利用气候反馈-响应分析方法进行分析,发现EUTT-IUTT变化的模式间差异主要来自于大气动力过程,其次是云的短波辐射效应的贡献.地表潜热通量和云的长波辐射效应缩小了EUTT-IUTT变化的模式间差异.  相似文献   

2020年11月大气环流和天气分析     

南洋  饶晓琴  尤媛  关良 《气象》2021,(2):253-260

2020年11月大气环流的主要特征为:北半球极涡呈偶极分布,环流呈三波型,东亚大槽偏弱,南支槽偏弱,西太平洋副热带高压偏西偏强。全国平均降水量为16.9 mm,比常年同期(19.0 mm)偏少11%,月内17—19日出现了一次强雨雪天气过程,湖北恩施建始县和辽宁丹东出现大暴雨,黑龙江牡丹江、鸡西和七台河、内蒙古通辽和赤峰等地出现大暴雪或特大暴雪。全国平均气温为3.9℃,比常年同期(2.9℃)偏高1℃,11月共出现4次冷空气过程,其中1次为全国强冷空气过程(18—22日)。10—17日,大气扩散条件较为不利,华北中南部、黄淮西部、汾渭平原等地发生一次雾-霾天气过程。  相似文献   

基于Parsivel天气现象仪资料的郑州“7·20”罕见特大暴雨微物理特征分析          下载免费PDF全文

周丹  周淑玲  田金华 《气象与环境科学》2022,45(1):93-101

基于2016-2018年ECMWF模式温度预报和浙江省72个国家基本站观测资料,根据温度日变化特征,采用K-近邻(KNN)回归算法进行误差订正,改进浙江省172 h精细化温度预报。在KNN回归算法中,将模式起报时刻的温度视作“背景”,由模式预报减去起报时刻温度消除“背景”影响,得到温度日变化曲线,通过温度日变化曲线构建差异指标,选取历史相似个例。根据历史相似个例的误差特征,对温度预报进行订正,得到改进的温度预报。检验结果表明,KNN方案的温度预报平均绝对误差较ECMWF和30 d滑动平均误差订正方案(OCF)的分别减小26.2%和5.2%;日最高和最低温度预报误差绝对值小于2℃,准确率较ECMWF的分别提高14.8%和4.3%,较OCF的分别提高3.0%和1.3%。KNN方案对地形复杂地区的温度预报改进效果更为明显,对冷空气活动和夏季高温等天气过程预报改善效果也较稳定。  相似文献